Applied statistics series structural (5 Ergebnisse)
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Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2006
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paperback. Zustand: New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Paperback. Pub Date :2012-08-01 Pages: 453 Publisher: Higher Education Press title: Applied Statistics Series structural equation model: Mplus application (English) List Price: 79.00 yuan Author: Wang…Jichuan Press: Higher Education Press Publication Date :2012-08-01ISBN: 9787040348286 Words: Page: 453 Edition: 1 Format: Folio: 16 Weight: Editor's Summary Applied Statistics Series structural equation model: Mplus and application ( English version) systematic exposition of easy-to-understand manner the basic concepts of structural equation modeling and statistical principles. focusing on the practical application of the various structural equation model. Applied Statistics Series. structural equation model: Mplus application (English) internationally renowned SEM software Mplus. using real data to demonstrate a variety of common as well as some of the newly developed higher structural equation model. provide the appropriate Mplus program. and the detailed interpretation of the results of program output. Referring to Applied Statistics Series. structural equation model: the Mplus and Application (English) provided examples and the corresponding computer program. the reader will be able to own practice various SEM model. The book can be used as the School of Social Sciences and the School of Public Health graduate statistics and biostatistics professional undergraduate textbook as the related disciplines of researchers engaged in the statistical analysis tool. Catalog 1 Introduction1.1 Modelformulation1.1.1 Measurement model1.1.2 Structuralmodel1.1.3 Model formulation in equations1.2 Modelidentification1.3 Modelestimation1.4 Modelevaluation1.5 Modelmodification1.6 Computer programs for SEMAppendix 1.A Expressing variances and covariances among observed variables as functions of model parametersAppendix 1.B Maximum likelihood function for SEM2 Confirmatory factor analysis2.1 Basics ofCFA model2.2 CFA model with continuous indicators2.3 CFA model with non-normal and censoredcontinuous indicators2.3.1 Testingnon-normality2.3.2 CFA model with non-normalindicators2. 3.3 CFA model with censored data2.4 CFA model with categoricalindicators2.4.1 CFAmodelwithbinaryindicators '2 .4.2 CFA model with ordered categoricalindicators2.5 Higher order CFA modelAppendix 2.A BSI-18 instrumentAppendix 2.B Item reliabilityAppendix 2.C Cronbach's alpha coefficientAppendix 2. D Calculating probabilities using PROBIT regression Coefficients3 Structuralequations withlatent variables3.1 MIMIC model3.2 Structuralequationmodel3.3 Correcting for measurement errorsin single indicator variables3.4 TestinginteractionsinvolvinglatentvariablesAppendix 3.A Influence of measurement errors4 Latent growth models for longitudinal data analysis4.1 LinearLGM4.2 NonlinearLGM4. 3 Multi-processLGM4.4 Two-partLGM4.5 LGM with categoricaloutcomes5 Multi-groupmodeling5.1 Multi-group CFA model5.1.1 Multi-group first-order CFA5.1.2 Multi-group second-order CFA5.2 Multi-group SEM model5. 3 Multi-groupLGM6 Mixturemodeling6.1 LCAmodel6.1.1 ExampleofLCA6.1.2 Example of LCA model with covariates6.2 LTAmodel6.2.1 ExampleofLTA6.3 Growth mixture model6.3.1 Example of GMM6.4 Factor mixture modelAppendix 6.A Including covariate in the LTA model7 Sample size for structural equation modeling7.1 The rules of thumb for sample size needed for SEM7.2 Satorra and Saris's method for sample size estimation7.2.1 Application of Satorra and Saris's method to CFA model7.2.2 Application of Satorra and Saris's method to LGM7.3 Monte Carlo simulation for sample size estimation7.3.1 Application ofMonte Carlo simulation to the the CFA model7.3.2 Application of the Monte Carlo simulation to LGM the . ReferencesIndex author abstracts preambleFour Satisfaction guaranteed,or money back.
